MCP interview question · Most asked
What is the Model Context Protocol (MCP), and what problem does it solve?
Summary
MCP is an open protocol that standardises how AI applications connect to external tools and data. A system is wrapped once in an MCP server; any MCP-capable application (a host with an MCP client) can discover and use its tools, resources and prompts. It turns N apps × M custom integrations into N clients plus M servers.
Longer Answer
Before MCP, every AI app re-implemented integrations to the same systems (ticket trackers, wikis, databases), each with its own auth, pagination and error handling. MCP defines the messages (JSON-RPC 2.0), the lifecycle (initialisation and capability negotiation) and the primitives, so integrations become reusable components. The model side does not change: the host still passes tool definitions (name, description, JSON Schema) to the model; MCP standardises where those tools come from and how they are called.
Key Points
- Open protocol between AI apps and tools/data.
- Servers expose capabilities; hosts discover them at runtime.
- JSON-RPC 2.0 messages.
- N×M integrations become N+M.
Deep dive: AI Agents and MCP in Production
Explanation
What interviewers look for
The N×M framing, the host/client/server roles, and that MCP complements rather than replaces tool calling.
Follow-up questions
- When would you not use MCP?
- How does an MCP tool reach the model?